Papers
Topics
Authors
Recent
Assistant
AI Research Assistant
Well-researched responses based on relevant abstracts and paper content.
Custom Instructions Pro
Preferences or requirements that you'd like Emergent Mind to consider when generating responses.
Gemini 2.5 Flash
Gemini 2.5 Flash 70 tok/s
Gemini 2.5 Pro 41 tok/s Pro
GPT-5 Medium 37 tok/s Pro
GPT-5 High 34 tok/s Pro
GPT-4o 21 tok/s Pro
Kimi K2 191 tok/s Pro
GPT OSS 120B 448 tok/s Pro
Claude Sonnet 4.5 35 tok/s Pro
2000 character limit reached

Efficient Sub-pixel Motion Compensation in Learned Video Codecs (2507.21926v1)

Published 29 Jul 2025 in cs.MM and eess.IV

Abstract: Motion compensation is a key component of video codecs. Conventional codecs (HEVC and VVC) have carefully refined this coding step, with an important focus on sub-pixel motion compensation. On the other hand, learned codecs achieve sub-pixel motion compensation through simple bilinear filtering. This paper offers to improve learned codec motion compensation by drawing inspiration from conventional codecs. It is shown that the usage of more advanced interpolation filters, block-based motion information and finite motion accuracy lead to better compression performance and lower decoding complexity. Experimental results are provided on the Cool-chic video codec, where we demonstrate a rate decrease of more than 10% and a lowering of motion-related decoding complexity from 391 MAC per pixel to 214 MAC per pixel. All contributions are made open-source at https://github.com/Orange-OpenSource/Cool-Chic

Summary

We haven't generated a summary for this paper yet.

Lightbulb Streamline Icon: https://streamlinehq.com

Continue Learning

We haven't generated follow-up questions for this paper yet.

List To Do Tasks Checklist Streamline Icon: https://streamlinehq.com

Collections

Sign up for free to add this paper to one or more collections.

Github Logo Streamline Icon: https://streamlinehq.com
X Twitter Logo Streamline Icon: https://streamlinehq.com

Tweets

This paper has been mentioned in 1 post and received 0 likes.

Don't miss out on important new AI/ML research

See which papers are being discussed right now on X, Reddit, and more:

“Emergent Mind helps me see which AI papers have caught fire online.”

Philip

Philip

Creator, AI Explained on YouTube